The ongoing invasion of the Lyme disease bacteria, Borrelia burgdorferi (Bb), in the United States presents a significant public health risk as well a a unique opportunity to study the process of ongoing pathogen emergence. Lyme disease is the most prevalent vector-borne disease in the USA and is rapidly emerging out of two disease foci in the Northeast and Midwest. Despite its epidemiological importance, knowledge of the source and trajectory of the current Bb invasion remains speculative, restricted to anecdotal case reports, and limited entomological surveys. It is critical to determine the origin and pathway of the current invasion to inform predictions about areas of further spread and improve disease control efforts. Phylogeographic approaches enable high-resolution study of epidemiologically important pathogens and include powerful methods for reconstructing the history of pathogen invasion and inferring epidemic origins, routes of invasion, and rates of spatial spread. Further, advances in next-generation sequencing (NGS) has made the generation of whole genome sequences (WGS) at the population-level efficient and cost-effective for study of pathogen genomic variation on epidemic timescales. However, the power of NGS and recent advances in Bayesian phylogeography, have not yet been harnessed for population genomic study of Bb, nor to investigate the evolutionary dynamics of Bb emergence. This study seeks to reconstruct the invasion history of the Lyme disease spirochete, Borrelia burgdorferi (Bb), to better understand the ecological and environmental drivers of Bb emergence and to inform predictions about continued pathogen spread. The proposed research will (1) use novel hybrid capture methods to obtain WGS of Bb directly from field- collected tick samples and allows identification of genome wide Single Nucleotide Polymorphisms (SNPs) that will be used to (2) reconstruct the history of Bb emergence across two spatial scales. The proposed research provides an important training opportunity in field study design, pathogen genomics, and phylogeographic analysis.